Abstract—This study presents a 96-day longitudinal analysis of Secure Reliable Transport (SRT) protocol behavior in a production streaming environment between Iraq and Turkey, examining 262,672 transport metric samples and 5,033,104 system resource measurements collected between October 2025 and January 2026. The research addresses temporal patterns, system-resource relationships, attack vulnerability, and anomaly detection. Results reveal significant temporal variation: Negative Acknowledgment (NAK_rate) exhibits 7.6-fold hourly variation and 11.5-fold daily variation (p < 0.001), though with small effect sizes (η² < 0.04), indicating that temporal period explains less than 4% of total variance. Central Processing Unit (CPU) utilization emerges as the strongest system-level correlate of transport variation (r = 0.617 with NAK_rate). Controlled User Datagram Protocol (UDP) flood experiments at 500 packets per second cause CPU increases of 176%–806%, while Secure Reliable Transport (SRT) transport metrics change by only ±13%, demonstrating protocol resilience through the Automatic Repeat Request (ARQ) mechanism. An unexpected anomaly reaching 97.7% CPU enabled signature-based differentiation between attack types. A Z-score anomaly detection method (3σ) outperforms fixed thresholds, detecting all 7 security events. This study contributes the longest temporal characterization of SRT metrics reported to date, the first system-SRT correlation analysis, and the first controlled security assessment of SRT infrastructure. These findings provide actionable guidance for capacity planning, security hardening, and multi-metric monitoring of production SRT deployments.
 
Keywords—Secure Reliable Transport (SRT) protocol, live streaming, temporal analysis, time series decomposition, Distributed Denial-of-Service (DDoS) vulnerability, transport metrics, production monitoring, network security